The artificial intelligence (AI)-powered EchoGo Amyloidosis can reportedly detect cardiac amyloidosis by assessing a single echocardiogram.
The Food and Drug Administration (FDA) has granted Breakthrough Device Designation for EchoGo Amyloidosis (Ultromics), which provides artificial intelligence (AI) assessment of echocardiograms to help diagnose cardiac amyloidosis.
While cardiac amyloidosis can be challenging to diagnose due to a heterogenous array of subtypes, including ATTR amyloidosis (transthyretin amyloidosis) and AL amyloidosis (light chain amyloidosis), Ultromics said the EchoGo Amyloidosis modality (developed with support from Janssen Biotech, Inc.) can detect the condition based on one echocardiogram.
Ultromics and Janssen Biotech said the EchoGo Amyloidosis platform is an important innovation in diagnosing a disease that has five-year mortality rates ranging from 44 to 65 percent without early detection.
“While treatments exist to help slow or halt the progression of cardiac amyloidosis, underdiagnosis in the early stages of disease is a huge challenge,” noted Najat Khan, Ph.D., the chief data science officer and global head of Strategy and Operations at Janssen Research and Development, LLC. “When applied to routine tests like echocardiograms, artificial intelligence is demonstrating exciting potential to help facilitate earlier disease detection with the goal of connecting patients with treatment sooner and, ultimately, driving better health outcomes.”
Ultromics noted that EchoGo Amyloidosis platform is intended to be included within the company’s EchoGo Platform. Currently in the midst of preparing regulatory submission of the modality, Ultromics said the EchoGo Amyloidosis platform could receive clearance for commercialization by early 2024.
(Editor’s note: For related content, see “Study Finds AI More Effective Than Sonographer Interpretation of Cardiac Function on Echocardiograms” and “Adjunctive AI Software for Cardiac Ultrasound Gets FDA Nod.”)
Study Assesses Potential of Seven-Minute AI-Enhanced 3T MRI of the Shoulder
February 20th 2025Researchers found that the use of seven-minute threefold parallel imaging-accelerated deep learning 3T MRI had 89 percent sensitivity for supraspinatus-infraspinatus tendon tears and 93 percent sensitivity for superior labral tears.
The Reading Room: Artificial Intelligence: What RSNA 2020 Offered, and What 2021 Could Bring
December 5th 2020Nina Kottler, M.D., chief medical officer of AI at Radiology Partners, discusses, during RSNA 2020, what new developments the annual meeting provided about these technologies, sessions to access, and what to expect in the coming year.
Can CT-Based AI Provide Automated Detection of Colorectal Cancer?
February 14th 2025For the assessment of contrast-enhanced abdominopelvic CT exams, an artificial intelligence model demonstrated equivalent or better sensitivity than radiologist readers, and greater than 90 percent specificity for the diagnosis of colorectal cancer.